Trakki is a Python-based desktop application built with Tkinter that helps you effortlessly track your income, expenses, and savings goals. It also features a built-in AI Financial Coach powered by the Groq API to provide personalized financial insights and advice.
- Python 3.x: Core programming language.
- Tkinter: GUI framework for the desktop interface.
- Matplotlib: Data visualization for the financial dashboard.
- Groq API: Powers the AI Financial Coach for intelligent analysis.
- Requests: For handling API communication.
- Dashboard & Analytics: View your current balance, total income, expenses, and savings at a glance with visual charts.
- Expense & Income Tracking: Add, edit, and remove transactions to keep your finances up to date.
- Savings Goals: Set savings goals, track your progress, and manage funds dedicated to specific items.
- AI Financial Coach: Chat with a built-in AI assistant that analyzes your current financial data and provides actionable, personalized advice in English and Tagalog.
- Transaction History: Review all your past financial activities in a clean table view.
Trakki was developed as a modular desktop application using Python's Tkinter. The architecture is designed to separate the graphical interface (gui/) from the core application logic and data models (logic/).
I integrated matplotlib directly into the Tkinter main loop to provide real-time updates to the dashboard charts. For the AI component, I implemented a robust integration with the Groq API, ensuring that the financial coach has enough context from the user's data to provide meaningful, personalized advice.
Building Trakki provided deep insights into:
- State Management in Tkinter: Coordinating data across multiple views (Dashboard, Expenses, Savings) while keeping the UI responsive.
- Embedded Visualizations: Learning how to integrate Matplotlib canvases into Tkinter widgets for a seamless user experience.
- API Integration & Prompting: Crafting specific system prompts for the Groq API to ensure the AI remains focused on financial coaching and supports multi-lingual responses.
- Modular Project Structure: Organizing a Python project with multiple directories to maintain clean and readable code.
- Data Export: Adding functionality to export financial summaries to CSV or PDF.
- Multi-Currency Support: Allowing users to track transactions in different currencies with automatic conversion.
- Enhanced AI Insights: Providing proactive alerts and more complex budgeting strategies.
- Dark Mode: A toggleable dark theme for better visual comfort.
- Python 3.x installed on your system.
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Download the Project Extract the project files into a single folder on your computer.
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Install Dependencies Open your terminal/command prompt, navigate to the project folder, and run:
pip install -r requirements.txt
Alternatively, on Windows, you can run
install_dependencies.bat. -
Run the Application
python main.py
The AI Coach works out of the box with no configuration needed.
-Aldrsze.